627 research outputs found
Distributed Tree Kernels
In this paper, we propose the distributed tree kernels (DTK) as a novel
method to reduce time and space complexity of tree kernels. Using a linear
complexity algorithm to compute vectors for trees, we embed feature spaces of
tree fragments in low-dimensional spaces where the kernel computation is
directly done with dot product. We show that DTKs are faster, correlate with
tree kernels, and obtain a statistically similar performance in two natural
language processing tasks.Comment: ICML201
Encasement as a morphogenetic mechanism: The case of bending
We study how the encasement of a growing elastic bulk within a possibly
differently growing elastic coat may induce mechanical instabilities in the
equilibrium shape of the combined body. The inhomogeneities induced in an
incompressible bulk during growth are also discussed. These effects are
illustrated through a simple example in which a growing elastic cylinder may
undergo a shape transition towards a bent configuration.Comment: 17 pages, 3 figure
Parsing with CYK over Distributed Representations
Syntactic parsing is a key task in natural language processing. This task has
been dominated by symbolic, grammar-based parsers. Neural networks, with their
distributed representations, are challenging these methods. In this article we
show that existing symbolic parsing algorithms can cross the border and be
entirely formulated over distributed representations. To this end we introduce
a version of the traditional Cocke-Younger-Kasami (CYK) algorithm, called
D-CYK, which is entirely defined over distributed representations. Our D-CYK
uses matrix multiplication on real number matrices of size independent of the
length of the input string. These operations are compatible with traditional
neural networks. Experiments show that our D-CYK approximates the original CYK
algorithm. By showing that CYK can be entirely performed on distributed
representations, we open the way to the definition of recurrent layers of
CYK-informed neural networks.Comment: The algorithm has been greatly improved. Experiments have been
redesigne
Hidden scaling patterns and universality in written communication
The temporal statistics exhibited by written correspondence appear to be
media dependent, with features which have so far proven difficult to
characterize. We explain the origin of these difficulties by disentangling the
role of spontaneous activity from decision-based prioritizing processes in
human dynamics, clocking all waiting times through each agent's `proper time'
measured by activity. This unveils the same fundamental patterns in written
communication across all media (letters, email, sms), with response times
displaying truncated power-law behavior and average exponents near -3/2. When
standard time is used, the response time probabilities are theoretically
predicted to exhibit a bi-modal character, which is empirically borne out by
our new years-long data on email. These novel perspectives on the temporal
dynamics of human correspondence should aid in the analysis of interaction
phenomena in general, including resource management, optimal pricing and
routing, information sharing, emergency handling.Comment: 27 pages, 10 figure
New activity pattern in human interactive dynamics
We investigate the response function of human agents as demonstrated by
written correspondence, uncovering a new universal pattern for how the reactive
dynamics of individuals is distributed across the set of each agent's contacts.
In long-term empirical data on email, we find that the set of response times
considered separately for the messages to each different correspondent of a
given writer, generate a family of heavy-tailed distributions, which have
largely the same features for all agents, and whose characteristic times grow
exponentially with the rank of each correspondent. We furthermore show that
this universal behavioral pattern emerges robustly by considering weighted
moving averages of the priority-conditioned response-time probabilities
generated by a basic prioritization model. Our findings clarify how the range
of priorities in the inputs from one's environment underpin and shape the
dynamics of agents embedded in a net of reactive relations. These newly
revealed activity patterns might be present in other general interactive
environments, and constrain future models of communication and interaction
networks, affecting their architecture and evolution.Comment: 15 pages, 7 figure
On solutions of one-dimensional stochastic differential equations driven by stable LĂ©vy motion
AbstractWe consider the stochastic differential equation dXt= b(Xt)dZt, t⩾o,where b is a Borel measurable real function and Z is a symmetric α-stable Lévy motion. In Section 1 we study the convergence of certain functionals of Z and in particular, we extend Engelbert and Schmidt 0–1 law (for functionals of the Wiener process) to functionals of a symmetric α-stable Lévy motion with 1 < α ⩽ 2. In Section 2 we study the existence of weak solutions for the above equation. When 0 < α < 1 or 1 < α ⩽ 2 we prove a sufficient existence condition. In the case 1 < α ⩽ 2, we extend Engelbert and Schmidt's necessary and sufficient existence condition (for the equation driven by a Wiener process) to the above equation: we prove that, for every α there exists a nontrivial solution starting from α, if and only if |b| α is locally integrable. In Section 3 we study “local” solutions. We also prove a result relating “local” and “global” solutions
Intermittency in crystal plasticity informed by lattice symmetry
We develop a nonlinear, three-dimensional phase field model for crystal
plasticity which accounts for the infinite and discrete symmetry group G of the
underlying periodic lattice. This generates a complex energy landscape with
countably-many G-related wells in strain space, whereon the material evolves by
energy minimization under the loading through spontaneous slip processes
inducing the creation and motion of dislocations without the need of auxiliary
hypotheses. Multiple slips may be activated simultaneously, in domains
separated by a priori unknown free boundaries. The wells visited by the strain
at each position and time, are tracked by the evolution of a G-valued discrete
plastic map, whose non-compatible discontinuities identify lattice
dislocations. The main effects in the plasticity of crystalline materials at
microscopic scales emerge in this framework, including the long-range elastic
fields of possibly interacting dislocations, lattice friction, hardening,
band-like vs. complex spatial distributions of dislocations. The main results
concern the scale-free intermittency of the flow, with power-law exponents for
the slip avalanche statistics which are significantly affected by the symmetry
and the compatibility properties of the activated fundamental shears.Comment: 13 pages, 4 figure
Strain intermittency in shape-memory alloys
We study experimentally the intermittent progress of the mechanically induced
martensitic transformation in a Cu-Al-Be single crystal through a full-field
measurement technique: the grid method. We utilize an in- house, specially
designed gravity-based device, wherein a system controlled by water pumps
applies a perfectly monotonic uniaxial load through very small force
increments. The sample exhibits hysteretic superelastic behavior during the
forward and reverse cubic-monoclinic transformation, produced by the evolution
of the strain field of the phase microstructures. The in-plane linear strain
components are measured on the sample surface during the loading cycle, and we
characterize the strain intermittency in a number of ways, showing the
emergence of power-law behavior for the strain avalanching over almost six
decades of magnitude. We also describe the nonstationarity and the asymmetry
observed in the forward versus reverse transformation. The present experimental
approach, which allows for the monitoring of the reversible martensitic
transformation both locally and globally in the crystal, proves useful and
enhances our capabilities in the analysis and possible control of
transition-related phenomena in shape-memory alloys.Comment: Four supplementary video
Distributed Smoothed Tree Kernel
In this paper we explore
the possibility to merge the world of
Compositional Distributional Semantic
Models (CDSM) with Tree Kernels
(TK). In particular, we will introduce a
specific tree kernel (smoothed tree kernel,
or STK) and then show that is
possibile to approximate such kernel
with the dot product of two vectors
obtained compositionally from the sentences,
creating in such a way a new
CDSM
Exploiting Transitivity in Probabilistic Models for Ontology Learning
Capturing word meaning is one of the challenges of natural language processing (NLP). Formal models of meaning such as ontologies are knowledge repositories used in a variety of applications. To be effectively used, these ontologies have to be large or, at least, adapted to specific domains. Our main goal is to contribute practically to the research on ontology learning models by covering different aspects of the task.
We propose probabilistic models for learning ontologies that expands existing ontologies taking into accounts both corpus-extracted evidences and structure of the generated ontologies. The model exploits structural properties of target relations such as transitivity during learning. We then propose two extensions of our probabilistic models: a model for learning from a generic domain that can be exploited to extract new information in a specific domain and an incremental ontology learning system that put human validations in the learning loop. This latter provides a graphical user interface and a human-computer interaction workflow supporting the incremental leaning loop
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